Abstract: Mobile Ad hoc Networks (MANETs) are more vulnerable to attacks than the generic wireless network due to the lack of an underlying infrastructure and shared medium. Intrusion Detection System (IDS) provides an enhanced level of security to such networks. Application of Soft computing techniques to the detection process is proved to be more suitable as they have human-like decision-making capabilities. This paper proposes a hybrid intrusion detection system for MANETs that detects black hole attack, by combining anomaly and specification-approaches of IDS. The proposed system aims at designing two different IDS using the two fundamental soft computing mechanisms such as, Fuzzy and Genetic Algorithm (GA). The design of each IDS is tested with simulated MANETs for various traffic conditions. The performance of each system is compared based on the true and false positive rates. The experimental results show that the fuzzy based system produces 81.8% true positive rate and the GA based system results in a 100% efficient detection.(More)

Mobile Ad hoc Networks (MANETs) are more vulnerable to attacks than the generic wireless network due to the lack of an underlying infrastructure and shared medium. Intrusion Detection System (IDS) provides an enhanced level of security to such networks. Application of Soft computing techniques to the detection process is proved to be more suitable as they have human-like decision-making capabilities. This paper proposes a hybrid intrusion detection system for MANETs that detects black hole attack, by combining anomaly and specification-approaches of IDS. The proposed system aims at designing two different IDS using the two fundamental soft computing mechanisms such as, Fuzzy and Genetic Algorithm (GA). The design of each IDS is tested with simulated MANETs for various traffic conditions. The performance of each system is compared based on the true and false positive rates. The experimental results show that the fuzzy based system produces 81.8% true positive rate and the GA based system results in a 100% efficient detection.